---
title: "Okta Account Lockout Events"
excerpt: "Valid Accounts
, Default Accounts
"
categories:
  - Application
last_modified_at: 2020-07-21
toc: true
toc_label: ""
tags:
  - Valid Accounts
  - Default Accounts
  - Defense Evasion
  - Initial Access
  - Persistence
  - Privilege Escalation
  - Defense Evasion
  - Initial Access
  - Persistence
  - Privilege Escalation
  - Splunk Enterprise
  - Splunk Enterprise Security
  - Splunk Cloud
---

### :warning: WARNING THIS IS A EXPERIMENTAL analytic
We have not been able to test, simulate, or build datasets for this object. Use at your own risk. This analytic is **NOT** supported.


[Try in Splunk Security Cloud](https://www.splunk.com/en_us/products/cyber-security.html){: .btn .btn--success}

#### Description

Detect Okta user lockout events

- **Type**: [Anomaly](https://github.com/splunk/security_content/wiki/Detection-Analytic-Types)
- **Product**: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

- **Last Updated**: 2020-07-21
- **Author**: Rico Valdez, Splunk
- **ID**: 62b70968-a0a5-4724-8ac4-67871e6f544d


#### Annotations

<details>
  <summary>ATT&CK</summary>

<div markdown="1">


| ID             | Technique        |  Tactic             |
| -------------- | ---------------- |-------------------- |
| [T1078](https://attack.mitre.org/techniques/T1078/) | Valid Accounts | Defense Evasion, Initial Access, Persistence, Privilege Escalation |

| [T1078.001](https://attack.mitre.org/techniques/T1078/001/) | Default Accounts | Defense Evasion, Initial Access, Persistence, Privilege Escalation |

</div>
</details>


<details>
  <summary>Kill Chain Phase</summary>

<div markdown="1">

* Exploitation


</div>
</details>


<details>
  <summary>NIST</summary>

<div markdown="1">

* DE.CM



</div>
</details>

<details>
  <summary>CIS20</summary>

<div markdown="1">

* CIS 16



</div>
</details>

<details>
  <summary>CVE</summary>

<div markdown="1">


</div>
</details>

#### Search 

```
`okta` displayMessage="Max sign in attempts exceeded" 
| rename client.geographicalContext.country as country, client.geographicalContext.state as state, client.geographicalContext.city as city 
| table _time, user, country, state, city, src_ip 
| `okta_account_lockout_events_filter` 
```

#### Macros
The SPL above uses the following Macros:
* [okta](https://github.com/splunk/security_content/blob/develop/macros/okta.yml)

> :information_source:
> **okta_account_lockout_events_filter** is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

#### Required field
* _time
* displayMessage
* client.geographicalContext.country
* client.geographicalContext.state
* client.geographicalContext.city


#### How To Implement
This search is specific to Okta and requires Okta logs are being ingested in your Splunk deployment.

#### Known False Positives
None. Account lockouts should be followed up on to determine if the actual user was the one who caused the lockout, or if it was an unauthorized actor.

#### Associated Analytic story
* [Suspicious Okta Activity](/stories/suspicious_okta_activity)




#### RBA

| Risk Score  | Impact      | Confidence   | Message      |
| ----------- | ----------- |--------------|--------------|
| 25.0 | 50 | 50 | tbd |


> :information_source:
> The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author. 

#### Reference


#### Test Dataset
Replay any dataset to Splunk Enterprise by using our [replay.py](https://github.com/splunk/attack_data#using-replaypy) tool or the [UI](https://github.com/splunk/attack_data#using-ui).
Alternatively you can replay a dataset into a [Splunk Attack Range](https://github.com/splunk/attack_range#replay-dumps-into-attack-range-splunk-server)



[*source*](https://github.com/splunk/security_content/tree/develop/detections/experimental/application/okta_account_lockout_events.yml) \| *version*: **2**